Daniel França Vasconcelos

Left ventricle segmentation in echocardiography using a radial-search-based image processing algorithm

A new left ventricle segmentation method in two-dimensional echocardiography images is proposed. Image processing techniques combined with radial search and temporal information are used to extract the left ventricle boundary. Borders from sequential images are extracted using the proposed method, and a curve illustrating the area variation within a cardiac cycle is presented. Performance evaluation is performed by comparing the borders obtained from the presented method to those manually prescribed by a medical specialist. The new sequential radial search algorithm improved the border extraction from long-axis ultrasound images, specially the ones where the mitral valve was open. Segmentation errors due to low contrast were corrected.

Semi-automatic detection of the left ventricular border

Two semi-automatic methods for the detection of the left ventricular border in two-dimensional short axis echocardiographic images are presented and compared. In these methods, the left ventricular area variation curve is calculated during a complete cardiac cycle after the segmentation of several frames. This allows the evaluation of the cardiovascular dynamics and the identification of important clinical parameters. The algorithms are proposed as several independent modules. The results are validated through the comparison between the semi-automatic continuous boundaries and manuals boundaries sketched by a medical specialist.

Semi-automatic algorithm for construction of the left ventricular area variation curve over a complete cardiac cycle

BackgroundTwo-dimensional echocardiography (2D-echo) allows the evaluation of cardiac structures and their movements. A wide range of clinical diagnoses are based on the performance of the left ventricle. The evaluation of myocardial function is typically performed by manual segmentation of the ventricular cavity in a series of dynamic images. This process is laborious and operator dependent. The automatic segmentation of the left ventricle in 4-chamber long-axis images during diastole is troublesome, because of the opening of the mitral valve.MethodsThis work presents a method for segmentation of the left ventricle in dynamic 2D-echo 4-chamber long-axis images over the complete cardiac cycle. The proposed algorithm is based on classic image processing techniques, including time-averaging and wavelet-based denoising, edge enhancement filtering, morphological operations, homotopy modification, and watershed segmentation. The proposed method is semi-automatic, requiring a single user intervention for identification of the position of the mitral valve in the first temporal frame of the video sequence. Image segmentation is performed on a set of dynamic 2D-echo images collected from an examination covering two consecutive cardiac cycles.ResultsThe proposed method is demonstrated and evaluated on twelve healthy volunteers. The results are quantitatively evaluated using four different metrics, in a comparison with contours manually segmented by a specialist, and with four alternative methods from the literature. The methods intra- and inter-operator variabilities are also evaluated.ConclusionsThe proposed method allows the automatic construction of the area variation curve of the left ventricle corresponding to a complete cardiac cycle. This may potentially be used for the identification of several clinical parameters, including the area variation fraction. This parameter could potentially be used for evaluating the global systolic function of the left ventricle.

Cystatin C, CRP, Log TG/HDLc and Metabolic Syndrome are Associated with Microalbuminuria in Hypertension

Background In patients with systemic hypertension, microalbuminuria is a marker of endothelial damage and is associated with an increased risk for cardiovascular disease. Objective To determine the factors that may lead to the occurrence of microalbuminuria in hypertensive patients with serum creatinine lower than 1.5 mg/dL. Methods This cross-sectional study included 133 Brazilians with essential hypertension followed up at a hypertension outpatient clinic. Those with serum creatinine higher than 1.5 mg/dL, as well as those with diabetes mellitus, were excluded. Systolic and diastolic blood pressures were measured, and body mass index (BMI) and GFR estimated by using the CKD-EPI formula were calculated. The serum levels of the following were assessed: CysC, creatinine, total cholesterol, HDL cholesterol, LDL cholesterol, triglycerides, C-reactive protein (CRP) and fasting glucose. Microalbuminuria was determined in 24-hour urine. Hypertensive patients were classified according to the presence of one or more criteria for metabolic syndrome. Results In a multiple regression analysis, the serum levels of CysC and CRP, the atherogenic index log TG/HDLc and the presence of three or more criteria for metabolic syndrome were positively correlated with microalbuminuria (r2: 0.277, p < 0.05). Conclusion CysC, CRP, log TG/HDLc, and the presence of three or more criteria for metabolic syndrome, regardless of serum creatinine, were associated with microalbuminuria, an early marker of kidney damage and cardiovascular risk in patients with essential hypertension.

On the use of motion-based frame rejection in temporal averaging denoising for segmentation of echocardiographic image sequences

We have recently introduced an algorithm for semi-automatic segmentation of the left ventricular wall in short-axis echocardiographic images (EMBC 30:218–221). In its preprocessing stage, the algorithm uses temporal averaging for image denoising. Motion estimation is used to detect and reject frames that do not correlate well with the set of images being averaged. However, the process of estimating motion vectors is computationally intense, which increases the algorithms computation time. In this work, we evaluate the viability of replacing the motion estimation stage with less computationally intense approaches. Two alternative techniques are evaluated. The ventricular contours obtained from each of the three algorithm variants were quantitatively and qualitatively compared with contours manually-segmented by a specialist. We show that it is possible to reduce the algorithms computational load without significantly reducing the segmentation quality. The proposed algorithms are also compared with three other techniques from the literature.

An Update on Doppler Ultrasound of Vertebral Arteries: Subclavian Steal Syndrome

A sindrome do roubo da subclavia refere-se a uma desordem vascular na qual ocorre inversao do fluxo de sangue da arteria vertebral ipsilateral, decorrente de uma estenose proximal a sua origem, geralmente uma oclusao da arteria subclavia ou, mais raramente, do tronco braquiocefalico. E uma doenca relativamente rara, relatada em aproximadamente 6% dos pacientes assintomaticos com sopros cervicais. O Doppler pulsado (PW) e util na analise da arteria vertebral, registrando informacoes capazes de identificar a presenca da Sindrome do Roubo da Subclavia. Com base nas alteracoes hemodinâmicas da arteria vertebral avaliadas pelo estudo com Doppler espectral, pode ser classificada nos tipos 1 (oculto), 2 (intermitente ou parcial) e 3 (completo). Com o advento da angioplastia transluminal percutânea e, em seguida, dos stents, muitos advogam essa combinacao de procedimentos como o tratamento de escolha dos casos sintomatico dessa sindrome.